[Combined Analysis of Dyslipidemia and Tumor Markers for the Diagnosis of Gastric Cancer].
[OBJECTIVE] To investigate changes in serum lipid profile parameters combined with tumor markers in gastric cancer (GC) patients and their value in GC screening.
- 95% CI 0.734-0.850
- Sensitivity 78%
- Specificity 74%
APA
Lu J, Xu R, et al. (2026). [Combined Analysis of Dyslipidemia and Tumor Markers for the Diagnosis of Gastric Cancer].. Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition, 57(2), 435-440. https://doi.org/10.12182/20260360504
MLA
Lu J, et al.. "[Combined Analysis of Dyslipidemia and Tumor Markers for the Diagnosis of Gastric Cancer].." Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition, vol. 57, no. 2, 2026, pp. 435-440.
PMID
42021900
Abstract
[OBJECTIVE] To investigate changes in serum lipid profile parameters combined with tumor markers in gastric cancer (GC) patients and their value in GC screening.
[METHODS] A total of 100 patients diagnosed with GC at Renji Hospital (West) between May and September 2025 were consecutively enrolled as the GC group (54 cases in stage Ⅰ/Ⅱ and 46 cases in stage Ⅲ/Ⅳ). Additionally, 100 age- and sex-matched healthy individuals undergoing routine physical examinations were included as the healthy control (HC) group. The serum levels of nine lipid indicators (high-density lipoprotein cholesterol [HDL-C], low-density lipoprotein cholesterol [LDL-C], total cholesterol [TC], triglycerides [TG], small and dense low-density lipoprotein cholesterol [sdLDL-C], apolipoprotein [Apo] A1, ApoB, ApoC2, and ApoC3) and five tumor markers (carcinoembryonic antigen [CEA], carbohydrate antigen [CA] 19-9, CA50, CA242, and CA72-4) were measured using an automatic biochemical analyzer and an electrochemiluminescence instrument. Intergroup differences were analyzed using the Mann-Whitney test. A stepwise Fisher discriminant analysis was used to establish a screening model based on lipid profiles and tumor markers. Diagnostic performance was evaluated using receiver operating characteristic (ROC) curve analysis, and the model's diagnostic performance was validated using 30 GC patients and 30 healthy controls consecutively enrolled from September to December 2025.
[RESULTS] Compared with the HC group, the GC group showed significantly lower levels of ApoA1, ApoC3, TC, HDL-C, LDL-C, and sdLDL-C ( < 0.05), while CEA and CA50 levels were significantly higher ( < 0.05). Patients with stage Ⅲ-Ⅳ GC had lower levels of ApoA1, ApoB, TC, HDL-C, LDL-C, and sdLDL-C compared to those with stage Ⅰ-Ⅱ GC ( < 0.05). ROC analysis showed that among individual indicators, HDL-C had the highest diagnostic performance, with an area under the curve (AUC) of 0.797 (95% CI: 0.734-0.850), sensitivity of 78%, and specificity of 74%. The screening model including ApoA1, ApoC3, HDL-C, LDL-C, TC, sdLDL-C, CEA, CA50, and age achieved an AUC of 0.940 (95% CI: 0.891-0.971), with 83.75% sensitivity and 92.5% specificity, outperforming any single biomarker in diagnostic efficacy.
[CONCLUSION] The combined panel of ApoA1, ApoC3, HDL-C, LDL-C, TC, sdLDL-C, CEA, CA50 and age offers a potential auxiliary tool for detecting gastric cancer.
[METHODS] A total of 100 patients diagnosed with GC at Renji Hospital (West) between May and September 2025 were consecutively enrolled as the GC group (54 cases in stage Ⅰ/Ⅱ and 46 cases in stage Ⅲ/Ⅳ). Additionally, 100 age- and sex-matched healthy individuals undergoing routine physical examinations were included as the healthy control (HC) group. The serum levels of nine lipid indicators (high-density lipoprotein cholesterol [HDL-C], low-density lipoprotein cholesterol [LDL-C], total cholesterol [TC], triglycerides [TG], small and dense low-density lipoprotein cholesterol [sdLDL-C], apolipoprotein [Apo] A1, ApoB, ApoC2, and ApoC3) and five tumor markers (carcinoembryonic antigen [CEA], carbohydrate antigen [CA] 19-9, CA50, CA242, and CA72-4) were measured using an automatic biochemical analyzer and an electrochemiluminescence instrument. Intergroup differences were analyzed using the Mann-Whitney test. A stepwise Fisher discriminant analysis was used to establish a screening model based on lipid profiles and tumor markers. Diagnostic performance was evaluated using receiver operating characteristic (ROC) curve analysis, and the model's diagnostic performance was validated using 30 GC patients and 30 healthy controls consecutively enrolled from September to December 2025.
[RESULTS] Compared with the HC group, the GC group showed significantly lower levels of ApoA1, ApoC3, TC, HDL-C, LDL-C, and sdLDL-C ( < 0.05), while CEA and CA50 levels were significantly higher ( < 0.05). Patients with stage Ⅲ-Ⅳ GC had lower levels of ApoA1, ApoB, TC, HDL-C, LDL-C, and sdLDL-C compared to those with stage Ⅰ-Ⅱ GC ( < 0.05). ROC analysis showed that among individual indicators, HDL-C had the highest diagnostic performance, with an area under the curve (AUC) of 0.797 (95% CI: 0.734-0.850), sensitivity of 78%, and specificity of 74%. The screening model including ApoA1, ApoC3, HDL-C, LDL-C, TC, sdLDL-C, CEA, CA50, and age achieved an AUC of 0.940 (95% CI: 0.891-0.971), with 83.75% sensitivity and 92.5% specificity, outperforming any single biomarker in diagnostic efficacy.
[CONCLUSION] The combined panel of ApoA1, ApoC3, HDL-C, LDL-C, TC, sdLDL-C, CEA, CA50 and age offers a potential auxiliary tool for detecting gastric cancer.
MeSH Terms
Humans; Stomach Neoplasms; Biomarkers, Tumor; Dyslipidemias; Female; Male; Middle Aged; CA-19-9 Antigen; Antigens, Tumor-Associated, Carbohydrate; Aged; Lipids; Carcinoembryonic Antigen; Adult; Case-Control Studies; Apolipoprotein A-I; Cholesterol, LDL; Cholesterol, HDL; Triglycerides
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